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https://github.com/mikeroyal/Vulkan-Guide

Vulkan Guide
https://github.com/mikeroyal/Vulkan-Guide

List: Vulkan-Guide

awesome awesome-list awesome-resources computer-graphics gpgpu gpu gpu-programming graphics graphics-api graphics-programming opencl resources vulkan vulkan-api vulkan-compute-shaders vulkan-game-engine vulkan-library vulkan-sdk vulkan-synchronization

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Vulkan Guide

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README 

        


 

  


 Vulkan Guide




#### A guide covering Vulkan including the applications, libraries and tools that will make you a better and more efficient Vulkan development.



**Note: You can easily convert this markdown file to a PDF in [VSCode](https://code.visualstudio.com/) using this handy extension [Markdown PDF](https://marketplace.visualstudio.com/items?itemName=yzane.markdown-pdf).**





 

  





# Table of Contents



1. [Vulkan Learning Resources](https://github.com/mikeroyal/Vulkan-Guide#vulkan-learning-resources)



2. [Vulkan Tools, Libraries, and Frameworks](https://github.com/mikeroyal/Vulkan-Guide#vulkan-tools-libraries-and-frameworks)



3. [Game Development](https://github.com/mikeroyal/Vulkan-Guide#game-development)



4. [C/C++ Development](https://github.com/mikeroyal/Vulkan-Guide#cc-development)



5. [CUDA Development](https://github.com/mikeroyal/Vulkan-Guide#cuda-development)



6. [Julia Development](https://github.com/mikeroyal/Vulkan-Guide#julia-development)



# Vulkan Learning Resources

[Back to the Top](https://github.com/mikeroyal/Vulkan-Guide#table-of-contents)



[Vulkan®](https://www.khronos.org/vulkan/) is a modern cross-platform graphics and compute API that provides high-efficiency, cross-platform access to modern GPUs used in a wide variety of devices from PCs and consoles to mobile phones and embedded platforms. Vulkan is currently in development by the Khronos consortium.



[Khronos Group GitHub](https://github.com/KhronosGroup)



[Vulkan Documentation](https://github.com/KhronosGroup/Vulkan-Docs)



[HLSL to SPIR-V Feature Mapping Manual](https://github.com/microsoft/DirectXShaderCompiler/blob/master/docs/SPIR-V.rst)



[Vulkan GLSL Ray Tracing Emulator Tutorial](https://www.gsn-lib.org/docs/nodes/raytracing.php)



[Getting Started with Vulkan](https://vulkan-tutorial.com/)



[Vulkan Samples](https://github.com/KhronosGroup/Vulkan-Samples)



[Khronos Community Forums](https://community.khronos.org/)



# Vulkan Tools, Libraries, and Frameworks

[Back to the Top](https://github.com/mikeroyal/Vulkan-Guide#table-of-contents)



[Vulkan SDK](https://vulkan.lunarg.com) is a set of tools that enables Vulkan developers to develop Vulkan applications.



[SPIR-V](https://www.khronos.org/spir/) is a set of tools that enables high-level language front-ends to emit programs in a standardized intermediate form to be ingested by Vulkan, OpenGL or OpenCL drivers. It eliminates the need for high-level language front-end compilers in device drivers, significantly reducing driver complexity, enables a broad range of language and framework front-ends to run on diverse hardware architectures and encourages a vibrant ecosystem of open source analysis, porting, debug and optimization tools.



[SPIRV-Reflect](https://github.com/KhronosGroup/SPIRV-Reflect) is a lightweight library that provides a C/C++ reflection API for SPIR-V shader bytecode in Vulkan applications.



[Vulkan® Tools](https://github.com/KhronosGroup/Vulkan-Tools) is a project that provides Khronos official Vulkan Tools and Utilities for Windows, Linux, Android, and macOS.



[Vulkan-Hpp](https://github.com/KhronosGroup/Vulkan-Hpp) is a API that provides a header only C++ bindings for the Vulkan C API to improve the developers Vulkan experience without introducing CPU runtime cost. It adds features like type safety for enums and bitfields, STL container support, exceptions and simple enumerations.



[Vulkan® Memory Allocator (VMA)](https://gpuopen.com/vulkan-memory-allocator/) is a  library that provides a simple and easy to integrate API to help you allocate memory for Vulkan® buffer and image storage.



[AMD Open Source Driver for Vulkan®](https://gpuopen.com/amd-open-source-driver-for-vulkan/) is an open-source Vulkan driver for AMD Radeon™ graphics adapters on Linux®.



[NVIDIA® Nsight™ Visual Studio Edition](https://developer.nvidia.com/nsight-visual-studio-edition) is an application development environment for heterogeneous platforms which brings GPU computing into Microsoft Visual Studio. NVIDIA Nsight™ VSE allows you to build and debug integrated GPU kernels and native CPU code as well as inspect the state of the GPU and memory.



[Radeon™ GPU Profiler](https://gpuopen.com/rgp/) is a performance tool that can be used by developers to optimize DirectX®12, Vulkan® and OpenCL™ applications for AMD RDNA™ and GCN hardware.



[Radeon™ GPU Analyzer](https://gpuopen.com/rga/) is a compiler and code analysis tool for Vulkan®, DirectX®, OpenGL® and OpenCL™.



[Radeon™ Memory Visualizer (RMV)](https://gpuopen.com/rmv/) is a tool provided by AMD for use by game engine developers. It allows engineers to examine, diagnose, and understand the GPU memory management within their projects.



[DXVK](https://github.com/doitsujin/dxvk) is a Vulkan-based translation layer for Direct3D 9/10/11 which allows running 3D applications on Linux using Wine.



[MoltenVK](https://moltengl.com/moltenvk) is an implementation of Vulkan running on iOS and macOS using Apple's [Metal](https://developer.apple.com/metal/) graphics framework.



[RenderDoc](https://renderdoc.org) is a stand-alone graphics debugger that allows quick and easy single-frame capture and detailed introspection of any application using Vulkan, D3D11, OpenGL & OpenGL ES or D3D12 across Windows, Linux, Android, Stadia, or Nintendo Switch™.



[PerfDoc](https://github.com/ARM-software/perfdoc) is a cross-platform Vulkan layer which checks Vulkan applications for [best practices on Arm Mali](https://developer.arm.com/graphics/developer-guides/mali-gpu-best-practices) devices.



[GLFW](https://www.glfw.org/) is an Open Source, multi-platform library for OpenGL, OpenGL ES and Vulkan application development. It provides a simple, platform-independent API for creating windows, contexts and surfaces, reading input, handling events, etc. GLFW natively supports Windows, macOS and Linux and other Unix-like systems. On Linux both X11 and Wayland are supported.



[VulkanSharp](https://github.com/mono/VulkanSharp) is a project provides a .NET binding for the Vulkan API.



[Vortice.Vulkan](https://github.com/amerkoleci/Vortice.Vulkan) is a .NET Standard 2.0 and .NET5 low-level bindings for Vulkan API.



[VKD3D-Proton](https://github.com/HansKristian-Work/vkd3d-proton) is a fork of VKD3D, which aims to implement the full Direct3D 12 API on top of Vulkan.



[ImGui](https://github.com/ocornut/imgui) is a bloat-free graphical user interface library for C++. It outputs optimized vertex buffers that you can render anytime in your 3D-pipeline enabled application. It is fast, portable, renderer agnostic and self-contained (no external dependencies).



[Ash](https://github.com/MaikKlein/ash) is a very lightweight wrapper around Vulkan.



[gfx-rs](https://github.com/gfx-rs/gfx) is a low-level, cross-platform graphics and compute abstraction library in Rust.



[Vulkan.jl](https://github.com/JuliaGPU/Vulkan.jl) is a lightweight wrapper around the Vulkan graphics and compute library. It exposes abstractions over the underlying C interface, primarily geared towards developers looking for a more natural way to work with Vulkan with minimal overhead.



# Game Development

[Back to the Top](https://github.com/mikeroyal/Vulkan-Guide#table-of-contents)





 

  







 

  





## Game Engines



**[Checkout the Unity Engine](https://unity.com/)**






**[Checkout the Unreal Engine 4](https://www.unrealengine.com/)**






**[Checkout the CryEngine](https://www.cryengine.com/)**






**[Checkout the Godot Engine](https://godotengine.org/)**



[If you would like to Donate to the Godot Project](https://www.patreon.com/godotengine)






**[Checkout Blender](https://www.blender.org/)**



[If you would like to Donate to the Blender Project](https://fund.blender.org/)






**[Checkout AWS Lumberyard(based on CryEngine)](https://aws.amazon.com/lumberyard/)**






**[Checkout Game Maker Studio 2](https://www.yoyogames.com/gamemaker)**






## Game Development Learning Resources



[Unreal Online Learning](https://www.unrealengine.com/en-US/onlinelearning-courses) is a free learning platform that offers hands-on video courses and guided learning paths.



[Unreal Engine Authorized Training Program](https://www.unrealengine.com/en-US/training-partners)



[Unreal Engine for education](https://www.unrealengine.com/en-US/education/)



[Unreal Engine Training & Simulation](https://www.unrealengine.com/en-US/industry/training-simulation)



[Unity Certifications](https://unity.com/products/unity-certifications)



[Autodesk for Games](https://www.autodesk.com/campaigns/autodesk-for-games)



[Getting Started with DirectX 12 Ultimate](https://devblogs.microsoft.com/directx/directx-12-ultimate-getting-started-guide/)



[Getting Started with Vulkan](https://www.khronos.org/vulkan/)



[Getting Started with Apple Metal](https://developer.apple.com/metal/)



[Game Design Online Courses from Udemy](https://www.udemy.com/courses/Design/Game-Design/)



[Game Design Online Courses from Skillshare](https://www.skillshare.com/browse/game-design)



[Learn Game Design with Online Courses and Classes from edX](https://www.edx.org/learn/game-design)



[Game Design Courses from Coursera](https://www.coursera.org/courses?query=game%20design)



[Game Design and Development Specialization Course from Coursera](https://www.coursera.org/specializations/game-development)



## Game Development Tools



[Unreal Engine](https://www.unrealengine.com) is a game engine developed by Epic Games with the world's most open and advanced real-time 3D creation tool. Continuously evolving to serve not only its original purpose as a state-of-the-art game engine, today it gives creators across industries the freedom and control to deliver cutting-edge content, interactive experiences, and immersive virtual worlds.



[Unity](https://unity.com) is a cross-platform game development platform. Use Unity to build high-quality 3D and 2D games, deploy them across mobile, desktop, VR/AR, consoles or the Web, and connect with loyal and enthusiastic players and customers.



[Unigine](https://unigine.com) is a cross-platform game engine designed for development teams (C++/C# programmers, 3D artists) working on interactive 3D apps.



[Panda3D](https://www.panda3d.org/) is a game engine, a framework for 3D rendering and game development for Python and C++ programs, developed by Disney and CMU. Panda3D is open-source and free for any purpose, including commercial ventures.



[Source 2](https://developer.valvesoftware.com/wiki/Source_2) is a 3D video game engine in development by Valve as a successor to Source. It is used in Dota 2, Artifact, Dota Underlords, parts of The Lab, SteamVR Home, and Half-Life: Alyx.



[Havok](https://www.havok.com/) is a middleware software suite that provides a realistic physics engine component and related functions to video games. It is supported  and optimized across all major platforms, including Nintendo Switch, PlayStation®, Stadia, and Xbox. Along with integrations for Unity and Unreal Engine and are used in countless proprietary game engines.



[AutoDesk 3ds Max](https://www.autodesk.com/products/3ds-max/overview) is a professional software program for 3D modeling, animation, rendering, and visualization. 3ds Max allows you to create stunning game environments, design visualizations, and virtual reality experiences.



[Houdini](https://www.sidefx.com/) is a 3D procedural software for modeling, rigging, animation, VFX, look development, lighting and rendering in film, TV, advertising and video game pipelines.



[A-Frame](https://aframe.io) is a web framework for building virtual reality experiences in WebVR with HTML and Entity-Component. A-Frame works on Vive, Rift, desktop, mobile platforms.



[AppGameKit](https://www.appgamekit.com) is a powerful game development engine, ideal for Hobbyist and Indie developers. Where you can start coding in the easy to learn AppGameKit BASIC or use the libraries in C++ & XCode.



[Amazon Lumberyard](https://aws.amazon.com/lumberyard/) is an open source, AAA game engine(based on CryEngine) that gives you the tools you need to create high quality games. Deeply integrated with AWS and Twitch, Amazon Lumberyard includes full source code, allowing you to customize your project at any level.



[Blender](https://www.blender.org) is the free and open source 3D creation suite. It supports the entirety of the 3D pipeline—modeling, rigging, animation, simulation, rendering, compositing and motion tracking, video editing and 2D animation pipeline.



[CryEngine](https://www.cryengine.com) is a powerful real-time game development platform created by Crytek.



[GameMaker Studio 2](https://www.yoyogames.com/gamemaker) is the latest and greatest incarnation of GameMaker. It has everything you need to take your idea from concept to finished game. With no barriers to entry and powerful functionality, GameMaker Studio 2 is the ultimate 2D development environment.



[Godot](https://godotengine.org) is a feature-packed, cross-platform game engine to create 2D and 3D games from a unified interface. It provides a comprehensive set of common tools, so that users can focus on making games without having to reinvent the wheel. Games can be exported in one click to a number of platforms, including the major desktop platforms (Linux, Mac OSX, Windows) as well as mobile (Android, iOS) and web-based (HTML5) platforms.



[Open Graphics Library(OpenGL)](https://www.opengl.org/) is an API used acrossed mulitple  programming languages and platforms for hardware-accelerated rendering of 2D/3D vector graphics currently developed by the [Khronos Group](https://www.khronos.org/).



[Open Computing Language (OpenCL)](https://www.khronos.org/opencl/) is an open standard for [parallel programming](https://www.coursera.org/lecture/parprog1/introduction-to-parallel-computing-zNrIS) of heterogeneous platforms consisting of CPUs, GPUs, and other hardware accelerators found in supercomputers, cloud servers, personal computers, mobile devices and embedded platforms.



[OpenGL Shading Language(GLSL)](https://www.khronos.org/opengl/wiki/Core_Language_(GLSL)) is a High Level Shading Language based on the C-style language, so it covers most of the features a user would expect with such a language.  Such as control structures (for-loops, if-else statements, etc) exist in GLSL, including the switch statement.



[High Level Shading Language(HLSL)](https://docs.microsoft.com/en-us/windows/win32/direct3dhlsl/dx-graphics-hlsl) is the High Level Shading Language for DirectX. Using HLSL, the user can create C-like programmable shaders for the Direct3D pipeline. HLSL was first created with DirectX 9 to set up the programmable 3D pipeline.



[DirectX 12 Ultimate](https://github.com/Microsoft/DirectX-Graphics-Samples) is an API(for high performance 2D & 3D graphics) from Microsoft. DirectX 12 Ultimate brings support for ray tracing, mesh shaders, variable rate shading, and sampler feedback. Available in Windows 2004 version(May 2020 Update).



[Vulkan](https://www.khronos.org/vulkan/) is a modern cross-platform graphics and compute API that provides high-efficiency, cross-platform access to modern GPUs used in a wide variety of devices from PCs and consoles to mobile phones and embedded platforms. Vulkan is currently in development by the Khronos consortium.



[Metal](https://developer.apple.com/metal/) is a low-level GPU programming framework used for rendering 2D and 3D graphics on Apple platforms such as iOS, iPadOS, macOS, watchOS and tvOS.



[MoltenVK](https://moltengl.com/moltenvk) is an implementation of Vulkan running on iOS and macOS using Apple's [Metal](https://developer.apple.com/metal/) graphics framework.



[MoltenGL](https://moltengl.com) is an implementation of the OpenGL ES 2.0 API that runs on Apple's [Metal](https://developer.apple.com/metal/) graphics framework.



[Mesa 3D Graphics Library](https://docs.mesa3d.org/index.html) is a project began as an open-source implementation of the OpenGL specification. A system for rendering interactive 3D graphics. Mesa ties into several other open-source projects: the [Direct Rendering Infrastructure](https://dri.freedesktop.org/), [X.org](https://x.org/), and [Wayland](https://wayland.freedesktop.org/) to provide OpenGL support on Linux, FreeBSD, and other operating systems.



[OpenGL ES](https://www.khronos.org/opengles/) is the mobile subset of OpenGL. It's supported on all major mobile platforms, and is also the base for WebGL.



[OpenCL](https://www.khronos.org/opencl/) is a framework for writing programs that execute across heterogeneous platforms consisting of CPUs, GPUs, DSPs, FPGAs and other processors or hardware accelerators.



[EGL](https://www.khronos.org/egl/) is an interface between Khronos rendering APIs such as OpenGL or OpenVG and the underlying native platform window system.



[VDPAU](https://www.freedesktop.org/wiki/Software/VDPAU/) is the Video Decode and Presentation API for UNIX. It provides an interface to video decode acceleration and presentation hardware present in modern GPUs.



[VA API](https://freedesktop.org/wiki/Software/vaapi/) is an open-source library and API specification, which provides access to graphics hardware acceleration capabilities for video processing.



[XvMC](https://en.wikipedia.org/wiki/X-Video_Motion_Compensation) is an extension of the X video extension (Xv) for the X Window System. The XvMC API allows video programs to offload portions of the video decoding process to the GPU hardware.



[AMD Radeon ProRender](https://www.amd.com/en/technologies/radeon-prorender) is a powerful physically-based rendering engine that enables creative professionals to produce stunningly photorealistic images on virtually any GPU, any CPU, and any OS in over a dozen leading digital content creation and CAD applications.



[NVIDIA Omniverse](https://developer.nvidia.com/nvidia-omniverse-platform) is a powerful, multi-GPU, real-time simulation and collaboration platform for 3D production pipelines based on Pixar's Universal Scene Description and NVIDIA RTX.



[LibGDX](https://github.com/libgdx/libgdx) is a cross-platform Java game development framework based on OpenGL (ES) that works on Windows, Linux, Mac OS X, Android, your WebGL enabled browser and iOS.



[cocos2d-x](https://github.com/cocos2d/cocos2d-x) is a multi-platform framework for building 2d games, interactive books, demos and other graphical applications. It is based on cocos2d-iphone, but instead of using Objective-C, it uses C++. It works on iOS, Android, macOS, Windows and Linux.



[MonoGame](https://github.com/MonoGame/MonoGame) is a framework for creating powerful cross-platform games. The spiritual successor to XNA with thousands of titles shipped across desktop, mobile, and console platforms. MonoGame is a fully managed .NET open source game framework without any black boxes.



[Three.js](https://threejs.org) is a cross-browser JavaScript library and application programming interface used to create and display animated 3D computer graphics in a web browser using WebGL.



[Superpowers](http://superpowers-html5.com/) is a downloadable HTML5 app for real-time collaborative projects . You can use it solo like a regular offline game maker, or setup a password and let friends join in on your project through their Web browser.



[URHO3D](https://urho3d.github.io/) is a free lightweight, cross-platform 2D and 3D game engine implemented in C++ and released under the MIT license. Greatly inspired by OGRE and Horde3D.



[Vivox](https://www.vivox.com/) is a voice & text chat platform that's trusted by the world's biggest gaming brands and titles such as Fortnite, PUBG, League of Legends, and Rainbow Six Siege.



[HGIG](https://www.hgig.org/) is a volunteer group of companies from the game and TV display industries that meet to specify and make available for the public guidelines to improve consumer gaming experiences in HDR.



[GameBlocks](https://www.gameblocks.com/) is a Server Side Anti-Cheat & Middleware software.



## Augmented Reality (AR) & Virtual Reality (VR)



[ARKit](https://developer.apple.com/augmented-reality/arkit/) is a set set of software development tools to enable developers to build augmented-reality apps for iOS developed by Apple. The latest version ARKit 3.5 takes advantage of the new LiDAR Scanner and depth sensing system on iPad Pro(2020) to support a new generation of AR apps that use Scene Geometry for enhanced scene understanding and object occlusion.



[RealityKit](https://developer.apple.com/documentation/realitykit) is a framework to implement high-performance 3D simulation and rendering with information provided by the ARKit framework to seamlessly integrate virtual objects into the real world.



[SceneKit](https://developer.apple.com/scenekit/) is a high-level 3D graphics framework that helps you create 3D animated scenes and effects in your iOS apps.



[ARCore](https://developers.google.com/ar/) is a software development kit developed by Google that allows for augmented reality applications in the real world. These tools include environmental understanding, which allows devices to detect horizontal and vertical surfaces and planes. It also includes motion tracking, which lets phones understand and track their positions relative to the world. Also ARCore’s Light Estimation API lets your digital objects appear realistically as if they’re actually part of the physical world.













Microsoft HoloLens Headset. Source: [Microsoft](https://www.microsoft.com/en-us/hololens/buy)













PlayStation VR Headset. Source: [PlayStation](https://www.playstation.com/en-us/ps-vr/)



[SteamVR](https://store.steampowered.com/steamvr) is the ultimate tool for experiencing VR content on the hardware of your choice. SteamVR supports the Valve Index, HTC Vive, Oculus Rift, Windows Mixed Reality headsets, and others.











SteamVR Home













Valve Index VR Headset. Source: [Steam](https://store.steampowered.com/valveindex)



[OpenVR](https://github.com/ValveSoftware/openvr) is an API and runtime that allows access to VR hardware(Steam Index, HTC Vive, and Oculus Rift) from multiple vendors without requiring that applications have specific knowledge of the hardware they are targeting.



[OpenVR Benchmark on Steam](https://store.steampowered.com/app/955610/OpenVR_Benchmark/) is the first benchmark tool for reproducibly testing your real VR performance, rendering inside of your VR headset.



[OpenHMD](http://www.openhmd.net/) is open source API and drivers that supports a wide range of HMD(head-mounted display) devices such as Oculus Rift, HTC Vive, Sony PSVR, and others.



[openXR](https://www.khronos.org/OpenXR/) is a free, open standard that provides high-performance access to Augmented Reality (AR) and Virtual Reality (VR) collectively known as XR—platforms and devices.



[Monado](https://monado.dev/) is the first OpenXR™ runtime for GNU/Linux. Monado aims to jump-start development of an open source XR ecosystem and provide the fundamental building blocks for device vendors to target the GNU/Linux platform.



[Libsurvive](https://github.com/cntools/libsurvive) is a set of tools and libraries that enable 6 dof tracking on lighthouse and vive based systems that is completely open source and can run on any device. It currently supports both SteamVR 1.0 and SteamVR 2.0 generation of devices and should support any tracked object commercially available.



[Simula](https://github.com/SimulaVR/Simula) is a VR window manager for Linux that runs on top of Godot. It takes less than 1 minute to install. Simula is officially compatible with SteamVR headsets equipped with Linux drivers (e.g. HTC Vive, HTC Vive Pro, & Valve Index). We have also added experimental support to OpenXR headsets that have Monado drivers (e.g. North Star, OSVR HDK, and PSVR). Some people have gotten the Oculus Rift S to run Simula via OpenHMD ([see here](https://github.com/OpenHMD/OpenHMD/issues/225#issuecomment-638454156)).



# C/C++ Development

[Back to the Top](https://github.com/mikeroyal/Vulkan-Guide#table-of-contents)





 

  





## C/C++ Learning Resources



[C++](https://www.cplusplus.com/doc/tutorial/) is a cross-platform language that can be used to build high-performance applications developed by Bjarne Stroustrup, as an extension to the C language.



[C](https://www.iso.org/standard/74528.html) is a general-purpose, high-level language that was originally developed by Dennis M. Ritchie to develop the UNIX operating system at Bell Labs. It supports structured programming, lexical variable scope, and recursion, with a static type system. C also provides constructs that map efficiently to typical machine instructions, which makes it one was of the most widely used programming languages today.



[Embedded C](https://en.wikipedia.org/wiki/Embedded_C) is a set of language extensions for the C programming language by the [C Standards Committee](https://isocpp.org/std/the-committee) to address issues that exist between C extensions for different [embedded systems](https://en.wikipedia.org/wiki/Embedded_system). The extensions hep enhance microprocessor features such as fixed-point arithmetic, multiple distinct memory banks, and basic I/O operations. This makes Embedded C the most popular embedded software language in the world.



[C & C++ Developer Tools from JetBrains](https://www.jetbrains.com/cpp/)



[Open source C++ libraries on cppreference.com](https://en.cppreference.com/w/cpp/links/libs)



[C++ Graphics libraries](https://cpp.libhunt.com/libs/graphics)



[C++ Libraries in MATLAB](https://www.mathworks.com/help/matlab/call-cpp-library-functions.html)



[C++ Tools and Libraries Articles](https://www.cplusplus.com/articles/tools/)



[Google C++ Style Guide](https://google.github.io/styleguide/cppguide.html)



[Introduction C++ Education course on Google Developers](https://developers.google.com/edu/c++/)



[C++ style guide for Fuchsia](https://fuchsia.dev/fuchsia-src/development/languages/c-cpp/cpp-style)



[C and C++ Coding Style Guide by OpenTitan](https://docs.opentitan.org/doc/rm/c_cpp_coding_style/)



[Chromium C++ Style Guide](https://chromium.googlesource.com/chromium/src/+/master/styleguide/c++/c++.md)



[C++ Core Guidelines](https://github.com/isocpp/CppCoreGuidelines/blob/master/CppCoreGuidelines.md)



[C++ Style Guide for ROS](http://wiki.ros.org/CppStyleGuide)



[Learn C++](https://www.learncpp.com/)



[Learn C : An Interactive C Tutorial](https://www.learn-c.org/)



[C++ Institute](https://cppinstitute.org/free-c-and-c-courses)



[C++ Online Training Courses on LinkedIn Learning](https://www.linkedin.com/learning/topics/c-plus-plus)



[C++ Tutorials on W3Schools](https://www.w3schools.com/cpp/default.asp)



[Learn C Programming Online Courses on edX](https://www.edx.org/learn/c-programming)



[Learn C++ with Online Courses on edX](https://www.edx.org/learn/c-plus-plus)



[Learn C++ on Codecademy](https://www.codecademy.com/learn/learn-c-plus-plus)



[Coding for Everyone: C and C++ course on Coursera](https://www.coursera.org/specializations/coding-for-everyone)



[C++ For C Programmers on Coursera](https://www.coursera.org/learn/c-plus-plus-a)



[Top C Courses on Coursera](https://www.coursera.org/courses?query=c%20programming)



[C++ Online Courses on Udemy](https://www.udemy.com/topic/c-plus-plus/)



[Top C Courses on Udemy](https://www.udemy.com/topic/c-programming/)



[Basics of Embedded C Programming for Beginners on Udemy](https://www.udemy.com/course/embedded-c-programming-for-embedded-systems/)



[C++ For Programmers Course on Udacity](https://www.udacity.com/course/c-for-programmers--ud210)



[C++ Fundamentals Course on Pluralsight](https://www.pluralsight.com/courses/learn-program-cplusplus)



[Introduction to C++ on MIT Free Online Course Materials](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-096-introduction-to-c-january-iap-2011/)



[Introduction to C++ for Programmers | Harvard ](https://online-learning.harvard.edu/course/introduction-c-programmers)



[Online C Courses | Harvard University](https://online-learning.harvard.edu/subject/c)



## C/C++ Tools and Frameworks



[Visual Studio](https://visualstudio.microsoft.com/) is an integrated development environment (IDE) from Microsoft; which is a feature-rich application that can be used for many aspects of software development. Visual Studio makes it easy to edit, debug, build, and publish your app. By using Microsoft software development platforms such as Windows API, Windows Forms, Windows Presentation Foundation, and Windows Store.



[Visual Studio Code](https://code.visualstudio.com/) is a code editor redefined and optimized for building and debugging modern web and cloud applications.



[Vcpkg](https://github.com/microsoft/vcpkg) is a C++ Library Manager for Windows, Linux, and MacOS.



[ReSharper C++](https://www.jetbrains.com/resharper-cpp/features/) is a Visual Studio Extension for C++ developers developed by JetBrains.



[AppCode](https://www.jetbrains.com/objc/) is constantly monitoring the quality of your code. It warns you of errors and smells and suggests quick-fixes to resolve them automatically. AppCode provides lots of code inspections for Objective-C, Swift, C/C++, and a number of code inspections for other supported languages. All code inspections are run on the fly.



[CLion](https://www.jetbrains.com/clion/features/) is a cross-platform IDE for C and C++ developers developed by JetBrains.



[Code::Blocks](https://www.codeblocks.org/) is a free C/C++ and Fortran IDE built to meet the most demanding needs of its users. It is designed to be very extensible and fully configurable. Built around a plugin framework, Code::Blocks can be extended with plugins.



[CppSharp](https://github.com/mono/CppSharp) is a tool and set of libraries which facilitates the usage of native C/C++ code with the .NET ecosystem. It consumes C/C++ header and library files and generates the necessary glue code to surface the native API as a managed API. Such an API can be used to consume an existing native library in your managed code or add managed scripting support to a native codebase.



[Conan](https://conan.io/) is an Open Source Package Manager for C++ development and dependency management into the 21st century and on par with the other development ecosystems.



[High Performance Computing (HPC) SDK](https://developer.nvidia.com/hpc) is a comprehensive toolbox for GPU accelerating HPC modeling and simulation applications. It includes the C, C++, and Fortran compilers, libraries, and analysis tools necessary for developing HPC applications on the NVIDIA platform.



[Thrust](https://github.com/NVIDIA/thrust) is a C++ parallel programming library which resembles the C++ Standard Library. Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs. Interoperability with established technologies such as CUDA, TBB, and OpenMP integrates with existing software.



[Boost](https://www.boost.org/) is an educational opportunity focused on cutting-edge C++. Boost has been a participant in the annual Google Summer of Code since 2007, in which students develop their skills by working on Boost Library development.



[Automake](https://www.gnu.org/software/automake/) is a tool for automatically generating Makefile.in files compliant with the GNU Coding Standards. Automake requires the use of GNU Autoconf.



[Cmake](https://cmake.org/) is an open-source, cross-platform family of tools designed to build, test and package software. CMake is used to control the software compilation process using simple platform and compiler independent configuration files, and generate native makefiles and workspaces that can be used in the compiler environment of your choice.



[GDB](http://www.gnu.org/software/gdb/) is a debugger, that allows you to see what is going on `inside' another program while it executes or what another program was doing at the moment it crashed.



[GCC](https://gcc.gnu.org/) is a compiler Collection that includes front ends for C, C++, Objective-C, Fortran, Ada, Go, and D, as well as libraries for these languages.



[GSL](https://www.gnu.org/software/gsl/) is a numerical library for C and C++ programmers. It is free software under the GNU General Public License. The library provides a wide range of mathematical routines such as random number generators, special functions and least-squares fitting. There are over 1000 functions in total with an extensive test suite.



[OpenGL Extension Wrangler Library (GLEW)](https://www.opengl.org/sdk/libs/GLEW/) is a cross-platform open-source C/C++ extension loading library. GLEW provides efficient run-time mechanisms for determining which OpenGL extensions are supported on the target platform.



[Libtool](https://www.gnu.org/software/libtool/) is a generic library support script that hides the complexity of using shared libraries behind a consistent, portable interface. To use Libtool, add the new generic library building commands to your Makefile, Makefile.in, or Makefile.am.



[Maven](https://maven.apache.org/) is a software project management and comprehension tool. Based on the concept of a project object model (POM), Maven can manage a project's build, reporting and documentation from a central piece of information.



[TAU (Tuning And Analysis Utilities)](http://www.cs.uoregon.edu/research/tau/home.php) is capable of gathering performance information through instrumentation of functions, methods, basic blocks, and statements as well as event-based sampling. All C++ language features are supported including templates and namespaces.



[Clang](https://clang.llvm.org/) is a production quality C, Objective-C, C++ and Objective-C++ compiler when targeting X86-32, X86-64, and ARM (other targets may have caveats, but are usually easy to fix). Clang is used in production to build performance-critical software like Google Chrome or Firefox.



[OpenCV](https://opencv.org/) is a highly optimized library with focus on real-time applications. Cross-Platform C++, Python and Java interfaces support Linux, MacOS, Windows, iOS, and Android.



[Libcu++](https://nvidia.github.io/libcudacxx) is the NVIDIA C++ Standard Library for your entire system. It provides a heterogeneous implementation of the C++ Standard Library that can be used in and between CPU and GPU code.



[ANTLR (ANother Tool for Language Recognition)](https://www.antlr.org/) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files. It's widely used to build languages, tools, and frameworks. From a grammar, ANTLR generates a parser that can build parse trees and also generates a listener interface that makes it easy to respond to the recognition of phrases of interest.



[Oat++](https://oatpp.io/) is a light and powerful C++ web framework for highly scalable and resource-efficient web application. It's zero-dependency and easy-portable.



[JavaCPP](https://github.com/bytedeco/javacpp) is a program that provides efficient access to native C++ inside Java, not unlike the way some C/C++ compilers interact with assembly language.



[Cython](https://cython.org/) is a language that makes writing C extensions for Python as easy as Python itself. Cython is based on Pyrex, but supports more cutting edge functionality and optimizations such as calling C functions and declaring C types on variables and class attributes.



[Spdlog](https://github.com/gabime/spdlog) is a very fast, header-only/compiled, C++ logging library.



[Infer](https://fbinfer.com/) is a static analysis tool for Java, C++, Objective-C, and C. Infer is written in [OCaml](https://ocaml.org/).



# CUDA Development

[Back to the Top](https://github.com/mikeroyal/Vulkan-Guide#table-of-contents)





 

  







 

  





**CUDA Toolkit. Source: [NVIDIA Developer CUDA](https://developer.nvidia.com/cuda-zone)**



## CUDA Learning Resources



[CUDA](https://developer.nvidia.com/cuda-zone) is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU, which is optimized for single-threaded. The compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers can program in popular languages such as C, C++, Fortran, Python and MATLAB.



[CUDA Toolkit Documentation](https://docs.nvidia.com/cuda/index.html)



[CUDA Quick Start Guide](https://docs.nvidia.com/cuda/cuda-quick-start-guide/index.html)



[CUDA on WSL](https://docs.nvidia.com/cuda/wsl-user-guide/index.html)



[CUDA GPU support for TensorFlow](https://www.tensorflow.org/install/gpu)



[NVIDIA Deep Learning cuDNN Documentation](https://docs.nvidia.com/deeplearning/cudnn/api/index.html)



[NVIDIA GPU Cloud Documentation](https://docs.nvidia.com/ngc/ngc-introduction/index.html)



[NVIDIA NGC](https://ngc.nvidia.com/) is a hub for GPU-optimized software for deep learning, machine learning, and high-performance computing (HPC) workloads.



[NVIDIA NGC Containers](https://www.nvidia.com/en-us/gpu-cloud/containers/) is a registry that provides researchers, data scientists, and developers with simple access to a comprehensive catalog of GPU-accelerated software for AI, machine learning and HPC. These containers take full advantage of NVIDIA GPUs on-premises and in the cloud.



## CUDA Tools Libraries, and Frameworks



[CUDA Toolkit](https://developer.nvidia.com/cuda-downloads) is a collection of tools & libraries that provide a development environment for creating high performance GPU-accelerated applications. The CUDA Toolkit allows you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms and HPC supercomputers. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library to build and deploy your application on major architectures including x86, Arm and POWER.



[NVIDIA cuDNN](https://developer.nvidia.com/cudnn) is a GPU-accelerated library of primitives for [deep neural networks](https://developer.nvidia.com/deep-learning). cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN accelerates widely used deep learning frameworks, including [Caffe2](https://caffe2.ai/), [Chainer](https://chainer.org/), [Keras](https://keras.io/), [MATLAB](https://www.mathworks.com/solutions/deep-learning.html), [MxNet](https://mxnet.incubator.apache.org/), [PyTorch](https://pytorch.org/), and [TensorFlow](https://www.tensorflow.org/).



[CUDA-X HPC](https://www.nvidia.com/en-us/technologies/cuda-x/) is a collection of libraries, tools, compilers and APIs that help developers solve the world's most challenging problems. CUDA-X HPC includes highly tuned kernels essential for high-performance computing (HPC).



[NVIDIA Container Toolkit](https://github.com/NVIDIA/nvidia-docker) is a collection of tools & libraries that allows users to build and run GPU accelerated Docker containers. The toolkit includes a container runtime [library](https://github.com/NVIDIA/libnvidia-container) and utilities to automatically configure containers to leverage NVIDIA GPUs.



[Minkowski Engine](https://nvidia.github.io/MinkowskiEngine) is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unpooling, and broadcasting operations for sparse tensors.



[CUTLASS](https://github.com/NVIDIA/cutlass) is a collection of CUDA C++ template abstractions for implementing high-performance matrix-multiplication (GEMM) at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS.



[CUB](https://github.com/NVIDIA/cub) is a cooperative primitives for CUDA C++ kernel authors.



[Tensorman](https://github.com/pop-os/tensorman) is a utility for easy management of Tensorflow containers by developed by [System76]( https://system76.com).Tensorman allows Tensorflow to operate in an isolated environment that is contained from the rest of the system. This virtual environment can operate independent of the base system, allowing you to use any version of Tensorflow on any version of a Linux distribution that supports the Docker runtime.



[Numba](https://github.com/numba/numba) is an open source, NumPy-aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the LLVM compiler project to generate machine code from Python syntax. Numba can compile a large subset of numerically-focused Python, including many NumPy functions. Additionally, Numba has support for automatic parallelization of loops, generation of GPU-accelerated code, and creation of ufuncs and C callbacks.



[Chainer](https://chainer.org/) is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using [CuPy](https://github.com/cupy/cupy) for high performance training and inference.



[CuPy](https://cupy.dev/) is an implementation of NumPy-compatible multi-dimensional array on CUDA. CuPy consists of the core multi-dimensional array class, cupy.ndarray, and many functions on it. It supports a subset of numpy.ndarray interface.



[CatBoost](https://catboost.ai/) is a fast, scalable, high performance [Gradient Boosting](https://en.wikipedia.org/wiki/Gradient_boosting) on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.



[cuDF](https://rapids.ai/) is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data. cuDF provides a pandas-like API that will be familiar to data engineers & data scientists, so they can use it to easily accelerate their workflows without going into the details of CUDA programming.



[cuML](https://github.com/rapidsai/cuml) is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn.



[ArrayFire](https://arrayfire.com/) is a general-purpose library that simplifies the process of developing software that targets parallel and massively-parallel architectures including CPUs, GPUs, and other hardware acceleration devices.



[Thrust](https://github.com/NVIDIA/thrust) is a C++ parallel programming library which resembles the C++ Standard Library. Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs.



[AresDB](https://eng.uber.com/aresdb/) is a GPU-powered real-time analytics storage and query engine. It features low query latency, high data freshness and highly efficient in-memory and on disk storage management.



[Arraymancer](https://mratsim.github.io/Arraymancer/) is a tensor (N-dimensional array) project in Nim. The main focus is providing a fast and ergonomic CPU, Cuda and OpenCL ndarray library on which to build a scientific computing ecosystem.



[Kintinuous](https://github.com/mp3guy/Kintinuous) is a real-time dense visual SLAM system capable of producing high quality globally consistent point and mesh reconstructions over hundreds of metres in real-time with only a low-cost commodity RGB-D sensor.



[GraphVite](https://graphvite.io/) is a general graph embedding engine, dedicated to high-speed and large-scale embedding learning in various applications.



# Julia Development

[Back to the Top](https://github.com/mikeroyal/Vulkan-Guide#table-of-contents)





 

  





# Julia Learning Resources



[Julia](https://julialang.org) is a high-level, [high-performance](https://julialang.org/benchmarks/) dynamic language for technical computing. Julia programs compile to efficient native code for [multiple platforms](https://julialang.org/downloads/#support_tiers) via LLVM.



[JuliaHub](https://juliahub.com/) contains over 4,000 Julia packages for use by the community.



[Julia Observer](https://www.juliaobserver.com)



[Julia Manual](https://docs.julialang.org/en/v1/manual/getting-started/)



[JuliaLang Essentials](https://docs.julialang.org/en/v1/base/base/)



[Julia Style Guide](https://docs.julialang.org/en/v1/manual/style-guide/)



[Julia By Example](https://juliabyexample.helpmanual.io/)



[JuliaLang Gitter](https://gitter.im/JuliaLang/julia)



[DataFrames Tutorial using Jupyter Notebooks](https://github.com/bkamins/Julia-DataFrames-Tutorial/)



[Julia Academy](https://juliaacademy.com/courses?preview=logged_out)



[Julia Meetup groups](https://www.meetup.com/topics/julia/)



[Julia on Microsoft Azure](https://juliacomputing.com/media/2017/02/08/azure.html)



# Julia Tools, Libraries and Frameworks



[JuliaPro](https://juliacomputing.com/products/juliapro.html) is a free and fast way to setup Julia for individual researchers, engineers, scientists, quants, traders, economists, students and others. Julia developers can build better software quicker and easier while benefiting from Julia's unparalleled high performance. It includes 2600+ open source packages or from a curated list of 250+ JuliaPro packages. Curated packages are tested, documented and supported by Julia Computing.



[Juno](https://junolab.org) is a powerful, free IDE based on [Atom](https://atom.io/) for the Julia language.



[Debugger.jl](https://github.com/JuliaDebug/Debugger.jl) is the Julia debuggin tool.



[Profile (Stdlib)](https://docs.julialang.org/en/v1/manual/profile/) is a module provides tools to help developers improve the performance of their code. When used, it takes measurements on running code, and produces output that helps you understand how much time is spent on individual line's.



[Revise.jl](https://github.com/timholy/Revise.jl) allows you to modify code and use the changes without restarting Julia. With Revise, you can be in the middle of a session and then update packages, switch git branches, and/or edit the source code in the editor of your choice; any changes will typically be incorporated into the very next command you issue from the REPL. This can save you the overhead of restarting Julia, loading packages, and waiting for code to JIT-compile.



[JuliaGPU](https://juliagpu.org/) is a Github organization created to unify the many packages for programming GPUs in Julia. With its high-level syntax and flexible compiler, Julia is well positioned to productively program hardware accelerators like GPUs without sacrificing performance.



[IJulia.jl](https://github.com/JuliaLang/IJulia.jl) is the Julia kernel for Jupyter.



[AWS.jl](https://github.com/JuliaCloud/AWS.jl) is a Julia interface for [Amazon Web Services](https://aws.amazon.com/).



[CUDA.jl](https://juliagpu.gitlab.io/CUDA.jl) is a package for the main programming interface for working with NVIDIA CUDA GPUs using Julia. It features a user-friendly array abstraction, a compiler for writing CUDA kernels in Julia, and wrappers for various CUDA libraries.



[XLA.jl](https://github.com/JuliaTPU/XLA.jl) is a package for compiling Julia to XLA for [Tensor Processing Unit(TPU)](https://cloud.google.com/tpu/).



[Nanosoldier.jl](https://github.com/JuliaCI/Nanosoldier.jl) is a package for running JuliaCI services on MIT's Nanosoldier cluster.



[Julia for VSCode](https://www.julia-vscode.org) is a powerful extension for the Julia language.



[JuMP.jl](https://jump.dev/) is a domain-specific modeling language for [mathematical optimization](https://en.wikipedia.org/wiki/Mathematical_optimization) embedded in Julia.



[Optim.jl](https://github.com/JuliaNLSolvers/Optim.jl) is a univariate and multivariate optimization in Julia.



[RCall.jl](https://github.com/JuliaInterop/RCall.jl) is a package that allows you to call R functions from Julia.



[JavaCall.jl](http://juliainterop.github.io/JavaCall.jl) is a package that allows you to call Java functions from Julia.



[PyCall.jl](https://github.com/JuliaPy/PyCall.jl) is a package that allows you to call Python functions from Julia.



[MXNet.jl](https://github.com/dmlc/MXNet.jl) is the Apache MXNet Julia package. MXNet.jl brings flexible and efficient GPU computing and state-of-art deep learning to Julia.



[Knet](https://denizyuret.github.io/Knet.jl/latest) is the [Koç University deep](http://www.ku.edu.tr/en) learning framework implemented in Julia by [Deniz Yuret](https://www.denizyuret.com/) and collaborators. It supports GPU operation and automatic differentiation using dynamic computational graphs for models defined in plain Julia.



[Distributions.jl](https://github.com/JuliaStats/Distributions.jl) is a Julia package for probability distributions and associated functions.



[DataFrames.jl](http://juliadata.github.io/DataFrames.jl/stable/) is a tool for working with tabular data in Julia.



[Flux.jl](https://fluxml.ai/) is an elegant approach to machine learning. It's a 100% pure-Julia stack, and provides lightweight abstractions on top of Julia's native GPU and AD support.



[IRTools.jl](https://github.com/FluxML/IRTools.jl) is a simple and flexible IR format, expressive enough to work with both lowered and typed Julia code, as well as external IRs.



[Cassette.jl](https://github.com/jrevels/Cassette.jl) is a Julia package that provides a mechanism for dynamically injecting code transformation passes into Julia’s just-in-time (JIT) compilation cycle, enabling post hoc analysis and modification of "Cassette-unaware" Julia programs without requiring manual source annotation or refactoring of the target code.



## Contribute



- [x] If would you like to contribute to this guide simply make a [Pull Request](https://github.com/mikeroyal/Vulkan-Guide/pulls).



## License

[Back to the Top](https://github.com/mikeroyal/Vulkan-Guide#table-of-contents)



Distributed under the [Creative Commons Attribution 4.0 International (CC BY 4.0) Public License](https://creativecommons.org/licenses/by/4.0/).